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Peter Shea: Does Online Learning Inhibit or Support Community College Student Success?
 

Peter Shea: Does Online Learning Inhibit or Support Community College Student Success?

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Dr. Peter Shea ...

Dr. Peter Shea
Does Online Learning Inhibit or Support Community College Student Success?
Using a nationally representative sample (The Beginning Postsecondary Student Survey, BPS 04/09), this study examined the associations between enrollment in credit-bearing distance education courses and degree attainment. We sought to determine whether US students enrolled in online/distance education courses during their first year of study at a community college tend to complete a degree (certificate, associate, or bachelor’s) at significantly lower rates than those who were not enrolled in such courses or programs. Unlike previous researchers, our findings indicated that students who take some of their early courses online or at a distance have a significantly better chance of attaining a community college credential than do their classroom-only counterparts. Implications for policy, practice, and theory related to student attrition, persistence, and success will be discussed.

presentation at the 15th annual SLN SOLsummit 2014 February 26, 2014
http://slnsolsummit2014.edublogs.org

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  • US is not producing sufficient numbers of college graduates Losing competitive advantage in the global economy (Hebel, 2006; Kelderman, 2013)Community Colleges:Six year national completion rates less than 20% Justifiably or not, community colleges are target of a great deal of criticismBut community colleges are crucial to supporting the US economy (College Board, 2008).
  • In 1985, Bean and Metzner developed a conceptual model, based on the Tinto model for non-traditional students. Learner characteristics for this model included age, enrollment status, residence, educational goals, high school performance, ethnicity, and gender. Academic variables included study habits, advising, absenteeism, certainty of major and course availability leading to academic outcomes (GPA). In place of the social supports of a campus, Bean and Metzner saw environmental factors such as finances, family responsibilities, employment responsibilities, and especially outside encouragement (from work and home) as being major determinants of psychological outcomes – utility of courses, satisfaction, goal commitment, and stress --which they in turn saw as a major determinant of the decision to drop-out. So for Bean & Metzner, learner characteristics, environmental variables and psychological outcomes (especially course satisfaction and perceived utility) were at the core of retention for non traditional students
  • Data: 24,000 students in 23 institutions in the Virginia Community College SystemOnline learning outcomes at community college worse than comparable classroom based outcomesSmith Jaggars & Xu, 2010; Xu & Smith Jaggars, 2011:Greater likelihood of failing or withdrawing from online courses than face-to-face coursesStudents who took online coursework in early semesters less likely to return in following semestersStudents w higher proportion of credits online less likely to attain a credential or transfer to a 4 year institution.
  • Data: N=51,000 in 34 institutions in Washington State Community College System (Xu & Smith Jaggars, 2011) Students with better educational preparation more likely to enroll in online courses… But significantly more likely to fail or withdraw from these courses than students who took face-to-face classesStudents who took more online courses less likely to complete a degree or transfer to a four-year college than those who took fewer online courses
  • Best evidence does not support strategy of increasing access to community college through online education. Given high costs associated with low completion rates online learning appears to produces more college students but fewer students with vital college credentials upon completion Online learning is less efficient and effective in achieving the goals of producing more college graduates in the US
  • Current study: build upon and add to the literature on the impacts of participation in online and distance education on community college degree completion Uses a national, rather than state samples of community college studentsDoes a national sample yield same results?
  • Does not account for other factors that contribute to higher success rates among online students Possible that initial differences among these two groups accounts for the higher degree completion rate. Took steps to control for initial differences between students in two groups
  • Matching in the propensity score approach attempts to mimic randomization in experimental designCreate a sample that received the treatment (DE) that is comparable on all observed covariates to a sample that did not receive the treatmentLook at differences between these matched samples
  • Higher Risk for dropout: Using an NCES derived risk category for drop out we found an overrepresentation of higher risk drop out among distance students on six of the seven variables that make up that category. Didn’t Attend Private High Schools: We also found that students who went to private high schools were underrepresented among those who took online and distance courses. Not better prepared? We therefore conclude that online and distance students appear to be no better academically prepared and possibly somewhat less prepared and/or less likely to graduate than students who did not take distance or online courses.
  • Net of the influence of the forty person,  family, and institutional covariates for which we controlled via propensity matching, students who had taken a distance or online course early in their academic careers were 1.25 times as likely to attain any degree as compared to those who had not taken a such a course. 
  • Despite potential initial disadvantage did not replicate findings that online/distance community college students were less likely to complete a college credential. National level data yields the opposite conclusion. Evidence suggests that early participation in online learning and distance education predicts higher rates of community college degree attainment.
  • Women overrepresented in DE/Online courses DE/Online students more likely to receive financial aid and have loansAn artifact of higher levels of enrollment in private, for profit institutions?For profits have demonstrated capacity to ensure DE students get maximum financial aid relative to public institutions (Clayton, 2011)Federal student loan data indicates students at for-profit institutions borrow more (and default more frequently) than those at public institutions (US Dept of Education, 2010)

Peter Shea: Does Online Learning Inhibit or Support Community College Student Success? Peter Shea: Does Online Learning Inhibit or Support Community College Student Success? Presentation Transcript

  • Dr. Peter Shea, Senior Researcher, SLN University at Albany, SUNY Dr. Temi Bidjerano Furman University
  •      Open SUNY – Open Journal Editor for the Journal of Asynchronous Learning Networks (JALN) Reinvigorating the journal You are invited! http://jaln.sloanconsortium.org/ Register to be considered as a reviewer  http://jaln.sloanconsortium.org/index.php/i ndex/user/register 
  •  What is it?
  • What is it?  “Avoidable” drop out? 
  • What is “access”?  “Full” benefits of higher education  Role of OLL in improving access to benefits  Previous theoretical and empirical work  New national study  › Question, methods, results, discussion
  • How do we measure access to HE?  Access to what?  What is the role of flexibility and convenience of online learning?  Has online learning improved access? How do we know?  Not as obvious as you might think… 
  •  Many (not all) of these benefits are contingent on completing a degree, not simply going to college…
  • US not producing sufficient numbers of college graduates  Losing competitive advantage in the global economy (Hebel, 2006; Kelderman, 2013)  Community Colleges:  › Six year national completion rates less than 20% › Justifiably or not, community colleges are target of criticism › But community colleges crucial to supporting US economy (College Board, 2008).
  • Spending on community college students has poor return on degree attainment  Delta project (Kirshtein & Wellman, 2012)  › “…half of instructional spending in community colleges goes to students (and credits) that do not attach to a degree or certificate” (p. 16) › Raises questions about efforts to increase access to community college students › Is it expensive and inefficient relative to benefits?
  •  Dramatic growth: 5.5-7M+ online enrollments in US  Most of them community college students but…  Does online learning merely increase the pool of a costly population of higher education learners who do not complete?  Crazy, right? Strong evidence that this may be the case…  But first, what theories inform research on degree completion?
  • Pre-entry Attributes Goals Institutional Experience Assumes these as “given” Integration Goals Outcome Why univariate outcome? Assumes these as “given” Where is institutional response? Where are “interventions”?
  •  „„We label none of the thirteen propositions of Tinto‟s theory as reliable knowledge [about] commuter colleges” (Braxton & Lee, 2005)
  • Assumes these as “given” academic variables academic outcomes learner characteristics decision to Drop-out environment environment al variables al variables psychological outcomes Assumes these as “given” Where is institutional response? Where are “interventions”?
  • Other Models: Falcone, 2012 Assumes these as “given” Multivariate Outcomes Assumes these as “given”
  •  What solid evidence do we have about online learning, degree completion, persistence, transfer etc?
  •  Online learning outcomes worse › Smith Jaggars & Xu, 2010; Xu & Smith Jaggars, 2011 Data: N=24,000 in 23 institutions in Virginia Community College System  More failing/withdrawing from online  Online students less likely to return  Students w higher proportion of credits online less likely to attain credential /transfer to 4 year institution 
  • Data: N=51,000 in 34 institutions in Washington State Community College System (Xu & Smith Jaggars, 2011)  Students with better preparation more likely to enroll in online courses…  But more likely to fail/withdraw  Students who took more online courses less likely to complete degree or transfer 
  • Best evidence does not support strategy of increasing access via online ed  Produces more college students but fewer with vital college credentials  OLL less efficient/effective in goal of producing more college grads in US  Questionable results re. “meaningful” access 
  • Our study uses a national, rather than state samples of community college students  Question: Does a national sample yield same results? 
  • Initial analysis of this NCES data revealed interesting patterns  Community College student seemed to do better with some distance courses  Even better when the courses were online … 
  • Cumulative persistence and attainment anywhere 2008-09 Attained Attained Attained No degree, bachelor's degree associate's degree certificate still enrolled No degree, left without return Total (%) (%) (%) (%) (%) 30.7 9.3 9.4 15 35.5 100% 8.9 13.5 9.6 8 15.1 14.3 35.2 38 100% 100% 0.37 0.38 0.55 0.65 Estimates Total Distance education 2004: Took courses No 31.2 Yes 26.3 Standard Error (BRR) Total 0.56 52% higher associates degree attainment?
  • Cumulative persistence and attainment anywhere 2008-09 Attained Attained bachelor's associate's degree degree Attained No degree, No degree, certificate still left enrolled without return Total (%) (%) (%) (%) (%) 30.7 9.3 9.4 15 35.5 100% Distance education used 2004: Internet No 31.2 Yes 25.5 8.9 14.1 9.6 7.3 15 15.1 35.3 38 100% 100% 0.37 0.38 0.55 0.65 Estimates Total Standard Error (BRR) Total 0.56 58% higher associates degree attainment?
  • Does not account for other factors  Possible that initial differences among these two groups accounts for the higher degree completion rate  Took steps to control for initial differences between students in two groups 
  • Degree attainment modeled as a function of enrollment in online/distance education courses at a community college  Controlling for a range of background characteristics 
  • (a) person variables: gender, age, race, risk index of dropping out (NCES derived), disability status, remedial coursework eligibility, traditional high school diploma or not (GED, certificate of completion, homeschooled), type of high school (public, private, other), total amount of loans during the first year etc.  (b) family variables: gross adjusted family income, parents‟ highest level of education, family size, siblings in college before respondent, parents taking college courses, parents‟ place of birth (U.S. vs. not);  (c) institutional variables: distance from home, historically black institution, Hispanic serving institution, accreditation, in-state institution, size of enrollment, percent of student body receiving federal grants, and type of institution (rural, suburban, urban or other). 
  • Matching attempts to mimic randomization in experimental design  Create a sample that received the treatment (DE/Online Ed)  Comparable on all 40 observed covariates to a sample that did not receive the treatment  Look at differences between these now matched samples 
  •  Data for BPS 04/09 collected from 16,100 first time beginning students at three points in time (in spring of 2004, 2006, 2009)  Participants in BPS represent target population of approximately 4,000,000 first time beginning post secondary students.  43.1% were first enrolled in two-year institutions offering associate‟s or certificate degree.
  • Net of 40 factors: More likely to take distance/online courses › Female students (p<.001), older students (p<.001), students from larger families (p<.05), students with a higher amount of institutional aid (p<.01) and loans (p<.05) › Students whose residence was at a greater distance from the institution › At greater risk of not completing a degree were somewhat more likely to be enrolled in distance education courses (p<.10). Net of 40 factors: Less likely to take distance/online courses › African –American students as compared to white students (p<.001) › Students who had indicated that location (p<.05) represents a reason for attending a particular institution.
  •  Positive Effects: › Number of months of full time enrollment increase the chances of degree attainment (B=.062, p<.001). › Students whose initial goal was to earn a certificate were about three times more likely to graduate (B = 1.168, p<.001)  Neutral Effects › No differences in the odds of degree completion between students with plans for a bachelor and those with a goal to earn an associate degree (B =.184, p>.05). › Number of institutions attended does not decrease the odds for degree (B = .072, n.s.).  Negative Effects › The number of periods of interruptions in continuous enrollment had a negative effect on the likelihood of degree attainment (B=-.232, p<.01)
  •  Distance Education Students: At higher risk for dropout  Didn‟t attend private high schools  Maybe not better prepared?  Despite this… 
  • Net of 40 other factors DE/online learners were 1.25 times as likely to attain any credential  When credential goal was certificate (rather than BA) DE/online learners were 3.22 times as likely to succeed 
  • Net of other differences the odds of graduating increase for students with early distance education coursework  Participation in online/distance learning does not appear to impede degree completion – perhaps facilitates it. 
  • Course Persistence Re-enrollment Preparedness or Transfer Degree Completion Virginia Study OLLs Lower OLLs Lower - OLLs Lower Washington Study OLLs Lower OLLs Lower OLLs more prepared OLLs Lower - OLLs same or less prepared? OLLs 1.25X3.2X Higher National Study - OLLs = Online Learners
  • Includes institutional response
  • Peter Shea, PhD Associate Professor Educational Theory and Practice & College of Computing and Information University at Albany, State University of New York pshea@albany.edu
  •  Several notable findings: › Unlike previous researchers (Xu & Smith Jaggars, 2010; Smith-Jaggars and Xu, 2011) › We did not find that students who participated in online/distance education were better-prepared academically › The online/distance students were about the same or maybe less well prepared
  • Despite potential initial disadvantage did not replicate findings that online/distance community college students were less likely to complete a college credential.  National level data yields the opposite conclusion.  Evidence suggests that early participation in online learning and distance education predicts higher rates of community college degree attainment. 
  •      Women overrepresented in DE/Online courses DE/Online students more likely to receive financial aid and have loans An artifact of higher levels of enrollment in private, for profit institutions? For profits have demonstrated capacity to ensure DE students get maximum financial aid relative to public institutions (Clayton, 2011) Federal student loan data indicates students at for-profit institutions borrow more (and default more frequently) than those at public institutions (US Dept of Education, 2010)